International Journal of Crowd Science 2019, 3(1): 63-86 https://doi.org/10.1108/IJCS-01-2019-0004

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A survey on VV&A of large-scale simulations

Show Author's Information Hide Author's Information Yanan Wang^¹, Jianqiang Li^¹, Sun Hongbo^²(

), Yuan Li^¹, Faheem Akhtar^³, Azhar Imran^⁴

Beijing University of Technology, Beijing, China

Yantai University, Yantai, China

Faculty of Information Technology, Beijing University of Technology, Beijing, China and Department of Computer Science, Sukkur IBA University, Sukkur, Pakistan

School of Software Engineering, Beijing University of Technology, Beijing, China

Keywords:

Large-scale simulation, Crowd network simulations, VV&A, Credibility

Cite this article:

Wang Y, Li J, Hongbo S, et al. A survey on VV&A of large-scale simulations. International Journal of Crowd Science, 2019, 3(1): 63-86. https://doi.org/10.1108/IJCS-01-2019-0004

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Abstract Full text About this article

Abstract

Purpose

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

Design/methodology/approach

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

Findings

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

Originality/value

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

Full text

Abstract

Full text

Outline

About this article

A survey on VV&A of large-scale simulations

Show Author's information Hide Author's Information Yanan Wang^¹, Jianqiang Li^¹, Sun Hongbo^²(

), Yuan Li^¹, Faheem Akhtar^³, Azhar Imran^⁴

Beijing University of Technology, Beijing, China

Yantai University, Yantai, China

Faculty of Information Technology, Beijing University of Technology, Beijing, China and Department of Computer Science, Sukkur IBA University, Sukkur, Pakistan

School of Software Engineering, Beijing University of Technology, Beijing, China

Abstract

Purpose

Design/methodology/approach

Findings

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

Originality/value

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

Keywords: Large-scale simulation, Crowd network simulations, VV&A, Credibility

References(99)

A, R.E. (1967), “Pattern recognition: theory, experiment, computer simulations, and dynamic models of form perception and discovery”, Brain Research, Vol. 2 No. 3, p. 299.

DOI Google Scholar

Abrahamson, G. (1980), “Terminology for model credibility”, Simulation, Vol. 35 No. 6, pp. 206-207.

DOI Google Scholar

Ahn, V.L. (2007), “Human computation”, Proceedings of the 4th International Conference on Knowledge Capture, K-CAP 2007, ACM, New York, NY, pp. 5-6.

Andrews, J. and Graef, S. (1970), “Dynamic modeling and simulation of the anaerobic digestion process”, Anaerobic Biological Treatment Processes, pp. 126-162.https://doi.org/10.1021/ba-1971-0105.ch008

DOI

Balci, O. (1994), “Validation, verification and testing through the life cycle of a simulation study”, Annals of Operations Research, Vol. 53 No. 1, pp. 121-173.

DOI Google Scholar

Balci, O. (1995), “Principles and techniques of simulation validation, verification, and testing”, Proceedings of the 27th Conference on Winter Simulation, IEEE Computer Society, pp. 147-154.https://doi.org/10.1145/224401.224456

DOI

Balci, O. (1997), “Verification validation and accreditation of simulation models”, in Proceedings of the 29th Conference on Winter Simulation, IEEE Computer Society, pp. 135-141.https://doi.org/10.1145/268437.268462

DOI

Balci, O. (1998), “Verification, validation, and testing”, Handbook of Simulation, Vol. 10, pp. 335-393.

Google Scholar

Balci, O. and Nance, R.E. (1985), “Formulated problem verification as an explicit requirement of model credibility”, Simulation, Vol. 45 No. 2, pp. 76-86.

DOI Google Scholar

Balci, O. and Sargent, R.G. (1982a), “Some examples of simulation model validation using hypothesis testing”, in Proceedings of the 14th Conference on Winter Simulation, Vol. 2, pp. 621-629.

Balci, O. and Sargent, R.G. (1982b), “Validation of multivariate response models using hoteling two-sample t2 test”, Simulation, Vol. 39 No. 6, pp. 185-192.

DOI Google Scholar

Balci, O. and Sargent, R.G. (1984), “Validation of simulation models via simultaneous confidence intervals”, American Journal of Mathematical and Management Sciences, Vol. 4 Nos 3/4, pp. 375-406.

DOI Google Scholar

Balci, O., Saadi, S.D. and Ormby, W.F. (2000), “Planning for verification, validation, and accreditation of modeling and simulation applications”, Simulation Conference, IEEE, pp. 829-839.

Barlas, Y. (1989), “Multiple tests for validation of system dynamics type of simulation models”, European Journal of Operational Research, Vol. 42 No. 1, pp. 59-87.

DOI Google Scholar

Barnes, C., Verdier, F., Pegatoquet, A., Gaffe, D. and Cottin, J.M. (2016), “Wireless sensor network protocol property validation through the system’s simulation in a dedicated framework”,10th International Conference on Signal Processing and Communication Systems, ICSPCS 2016 – Proceedings, available at: https://doi.org/10.1109/ICSPCS.2016.7843355

DOI

Bayarri, M.J., Berger, J.O., Paulo, R., Sacks, J., Cafeo, J.A., Cavendish, J., Lin, C.-H. and Tu, J. (2007), “A framework for validation of computer models”, Technometrics, Vol. 49 No. 2, pp. 138-154.

DOI Google Scholar

Birta, L.G. and Ozmizrak, F.N.J. (1996), “A knowledge-based approach for the validation of simulation models: the foundation”, ACM Transactions on Modeling and Computer Simulation, Vol. 6 No. 1, pp. 76-98.

DOI Google Scholar

Borko, H. (1962), Computer Applications in the Behavioral Sciences, Prentice Hall, Englewood.

Chai, Y., Miao, C., Sun, B., Zheng, Y. and Li, Q. (2017), “Crowd science and engineering: concept and research framework”, International Journal of Crowd Science, Vol. 1 No. 1, pp. 2-8.

DOI Google Scholar

Cooley, P. and Solano, E. (2011), “Agent-based model (ABM) validation considerations”, Proceedings of the Third International Conference on Advances in System Simulation (SIMUL 2011), IARIA, Barcelona, pp. 134-139.

Dean, S. (2004), “Verification and validation in military simulations”, Proceedings of the 2004 Winter Simulation Conference, pp. 925-932.

Department of Defense (1996), “Department of defense verification, validation, and accreditation (W and A) recommended practices guide”, Defense Modeling and Simulation Office, Alexandria, VA, November, in Balci, P.A., Glasow, P., Muessig, E.H., Page, J., Sikora, S., Solick, S. and Youngblood, S. (Eds), available at: http://triton.dmso.mil/docslib/mspolicy/vva/r

Department of Defense Instruction (DoDI) (2003), “DoD modeling and simulation verification, validation and accreditation”, available at: www.docin.com/p-116071952.html

Deslandres, V. and Pierreval, H. (1991), “An expert system prototype assisting the statistical validation of simulation models”, Simulation-Transactions of the Society for Modeling and Simulation International, Vol. 56 No. 2, pp. 79-89.

DOI Google Scholar

Drchal, J., Certický, M. and Jakob, M. (2016), “VALFRAM: validation framework for activity-based models”, Jasss, Vol. 19 No. 3, available at: https://doi.org/10.18564/jasss.3127

DOI Google Scholar

Easterling, R.G. (2001), “Measuring the predictive capability of computational methods: principles and methods, issues and illustrations”, Office of Scientific and Technical Information Technical Reports.https://doi.org/10.2172/780290

DOI

Eek, M., Kharrazi, S., Gavel, H. and Olvander, J. (2015), “Study of industrially applied methods for verification, validation and uncertainty quantification of simulator models”, International Journal of Modeling, Simulation, and Scientific Computing, Vol. 6 No. 2, p. 1550014.

DOI Google Scholar

Evans, G.W., Wallace, G.F. and Sutherland, G.L. (1967), “Simulation using digital computers”, Digital Simulation.

Fishman, G.S. and Kiviat, P.J. (1967), “The analysis of simulation–generated time series”, Management Science, Vol. 13 No. 7, pp. 525-557.

DOI Google Scholar

Glasow, P., Muessig, P., Sikora, J., Youngblood, S., Balci, O., Solick, S. and Page, E. (1996), “Verification, validation, and accreditation (VV&A) recommended practice guide”, Office of the Director of Defense Research and Engineering, Defense Modeling and Simulation Office.

Glasow, P., Muessig, P., Sikora, J., Youngblood, S., Balci, O., Solick, S. and Page, E. (2000), “Verification, validation, and accreditation (VV&A) recommended practice guide 2”, Office of the Director of Defense Research and Engineering, Defense Modeling and Simulation Office.

Glasow, P., Muessig, P., Sikora, J., Youngblood, S., Balci, O., Solick, S. and Page, E. (2005), “Verification, Validation, and Accreditation (VV&A) Recommended Practice Guide 2.5”, Office of the Director of Defense Research and Engineering, Defense Modeling and Simulation Office.

Goodman, C.J., Mellitt, B. and Rambukwella, N.B. (1987), “CAE for the electrical design of urban rail transit systems”, Computers in Railway Operations, pp. 173-193.

Gurcan, O., Dikenelli, O. and Bernon, C. (2011), “Towards a generic testing framework for agent-based simulation models”, Computer Science and Information Systems, IEEE, pp. 635-642.

Han, D. (2013), “Research and implementation on application software hybrid trust measurement”, working paper, Beijing University of Technology, Beijing, 15 June.

Howard, C.E. (2011), “Simulation and training: expecting the unexpected”, Military and Aerospace Electronics, Vol. 22 No. 11, pp. 12-14.

Google Scholar

Interactive, D. and Committee, S. (1998), “IEEE Trial-Use recommended practice for distributed interactive simulation verification, validation, accreditation, IEEE trial”, IEEE.

Interoperability, S., Committee, S. and Computer, I. (2007), “IEEE recommended practice for verification, validation, and accreditation of a federation – an overlay to the High-Level architecture federation development and execution process”.

Kheir, N.A. and Holmes, W.M. (1978), “On validating simulation models of missile systems”, SIMULATION, Vol. 30 No. 4, pp. 117-128.

DOI Google Scholar

Kheir, W.M. et al. (1986), “Flight mechanics panel working group WG-12 on validation of missile system simulation”, Advisory Group for Aerospace Research and Development Neuilly-Sur-Seine (France), available at: https://apps.dtic.mil/docs/citations/ADA166617

Kleijnen, J.P.C. (1999), “Validation of models, statistical techniques and data availability”, Simulation Conference IEEE.https://doi.org/10.1145/324138.324450

DOI

Klügl, F. (2008), “A validation methodology for agent-based simulations”, Proceedings of the 2008 ACM Symposium on Applied Computing, ACM, pp. 39-43.https://doi.org/10.1145/1363686.1363696

DOI

Klügl, F. (2009), “Agent-based simulation engineering”, PhD thesis, Habilitation Thesis, University of Wurzburg.

Law, A.M. (2007), Simulation Modeling and Analysis, 4th ed., McGraw-Hill, New York, NY.

Lent, M.V., Hill, R., McAlinden, R. and Brobst, P. (2003), “2002 Defense modeling and simulation office (DMSO) laboratory for human behavior model interchange standards”, University of Southern California Marina Del Rey CA Inst for Creative Technologies.

Li, H. and Sun, F. (2007), “A parallel multi-agent simulation planning approach to complex logistics system with genetic optimization”, International Conference on Wireless Communications, IEEE.https://doi.org/10.1109/WICOM.2007.1187

DOI

Li, L. (2012), “Research on simulation credibility assessment of marine electric propulsion system”, Working paper, Harbin Engineering University, Harbin.

Li-Ping, Z. and Xiao-Ping, L. (2007), “Research on operational validity evaluation of man-in-the-loop simulation system”, Journal of System Simulation, Vol. 19 No. 7, pp. 1417-1421.

Google Scholar

Liu, M. (2017), “Research on restful software credibility testing based on behavior declaration”, Working paper, Beijing University of Technology, Beijing, 25 May.

Louloudi, A. and Klügl, F. (2012), “Immersive face validation: a new validation technique for agent-based simulation”, Computer Science and Information Systems IEEE.

Lv, H. (2016), “Research on software credibility testing method based on behavior declaration”, Working paper, Beijing University of Technology, Beijing, 12 June.

McLeod, J. (1968), Simulation: The Dynamic Modeling of Ideas and Systems with Computers, McGraw-Hill.

Machlup, F. (1955), “The problem of verification in economics”, Southern Economic Journal, Vol. 22 No. 1, pp. 1-21.

DOI Google Scholar

Martin, F.F. (1968), Computer Modeling and Simulation, Wiley, New York, NY.

Mehrabadi, N.R., Wen, B., Burgos, R., Boroyevich, D. and Roy, C. (2014), “Verification, validation and uncertainty quantification (VV&UQ) framework applicable to power electronics systems”, SAE Technical Paper 2014-01-2176, available at: https://doi.org/10.4271/2014-01-2176

DOI

Miller, R.L. (1981), “Computer simulation in Geology”, Earth Science Reviews, Vol. 7 No. 3, pp. A130-A131.

DOI Google Scholar

Montanola-Sales, C., Onqqo, S. and Casanovas-Garcia, J. (2011), “Agent-based simulation validation: a case study in a demographic simulation”, Proceedings of the Third International Conference on Advances in System Simulation (SIMUL 2011), Barcelona, pp. 109-115.

Montgomery, D.C. and Conard, R.G. (1980), “Comparison of simulation and flight test data for missile systems”, SIMULATION: Transactions of the Society for Modeling and Simulation International, Vol. 34 No. 2, pp. 63-72.

DOI Google Scholar

Muessig, P.R. (2001), “A ‘smart’ approach to VV&A”.

Nan, Y., Liu, Y., Shen, J. and Chai, Y. (2017), “A study on the MCIN model in intelligent clothing industry”, International Journal of Crowd Science, Vol. 1 No. 2, pp. 133-145.

DOI Google Scholar

Niazi, M.A., Hussain, A. and Kolberg, M. (2009), “Verification and validation of agent-based simulations using the VOMAS (virtual overlay multi-agent system) approach”, CEUR Workshop Proceedings, Vol. 494, pp. 340-346.

Oberkampf, W.L. (1994), “A proposed framework for computational fluid dynamics code calibration/validation”, Nasa Sti/recon Technical Report N, 95.https://doi.org/10.2514/6.1994-2540

DOI

Oberkampf, W.L. and Barone, M.F. (2006), “Measures of agreement between computation and experiment: validation metrics”,Journal of Computational Physics, Vol. 217 No. 1, pp. 5-36.

DOI Google Scholar

Peng, P., Jian-Bing, T. and Ya-Bing, Z. (2017), “Amelioration and application of similar degree method for simulation credibility evaluation”, Journal of System Simulation, Vol. 19 No. 12, pp. 2658-2660.

Google Scholar

Pengfei, X., Lees, M., Nan, H. and Viswanthatn, T.V. (2011), “Validation of agent-based simulation through human computation: an example of crowd simulation”, International Conference on Multi-Agent-Based Simulation, Springer-Verlag, pp. 1-13.

Pidd, M. (2004), Computer Simulation in Management Science, John Wiley and Sons Inc, Indianapolis, IN.

Railsback, S.F. and Grimm, V. (2011), Agent-Based and Individual-Based Modeling: A Practical Introduction, Princeton University Press, Princeton, NJ.

Reid, J., Stone, K., Brown, J., Caglar, D., Kobayashi, A., Lewis-Newby, M. and Partridge, R. et al. (2012), “The Simulation Team Assessment Tool (STAT): development, reliability and validation”, Resuscitation, Vol. 83 No. 7, pp. 879-886. European Resuscitation Council, American Heart Association, Inc., and International Liaison Committee on Resuscitation. Elsevier Ireland Ltd.https://doi.org/10.1016/j.resuscitation.2011.12.012

DOI

Rothenberg, J. (1989), “The nature of modeling”, Artificial intelligence, simulation and modeling.https://doi.org/10.1145/76738.76743

DOI

Sanders, P. (1996), “DoD modeling and simulation (M&S) verification, validation, and accreditation (VV&A) (no. DODI-5000.61)”, Office of the Under Secretary of Defense (Acquisition And Technology), Washington, DC.https://doi.org/10.21236/ADA315867

DOI

Sargent, R., Glasow, P., Kleijnen, J., Law, A., McGregor, I. and Youngblood, S. (2000), “Strategic directions in verification, validation, and accreditation research”, Proceedings of the 2000 Winter Simulation Conference, pp. 909-916.

Sargent, R.G. (1997), “Verification, validation, and accreditation of simulation models”,Applied System Simulation, Vol. 1 No. 4, pp. 487-506.

Google Scholar

Sargent, R.G. (2001), “Some approaches and paradigms for verifying and validating simulation models”, Proceedings of the 2001 Winter Simulation Conference, IEEE.

Sargent, R.G. (2005), “Verification and validation of simulation models”, Proceedings of the 37th Conference on Winter Simulation, WSC’05, Winter Simulation Conference, 4-7 December, Orlando, FL, pp. 130-143.

Shangguan, W., Yuan, C.Y., Zhang, J.M., Cai, B.G. and Wang, J. (2014), “Verification and evaluation method of cooperative vehicle-infrastructure simulation system based on AHP-GRAP”, International Conference on Electromagnetics in Advanced Applications, IEEE.https://doi.org/10.1109/ICEAA.2014.6903921

DOI

Shannon, R. (1975), The Art and Science, Prentice Hall.

Shichman, H. and Hodges, D. (2003), “Modeling and simulation of insulated-gate field-effect transistor switching circuits”, IEEE Journal of Solid-State Circuits, Vol. 3 No. 3, pp. 285-289.

DOI Google Scholar

Sklar, E. (2007), “NetLogo, a multi-agent simulation environment”, Artificial Life, Vol. 13 No. 3, pp. 303-311.

DOI Google Scholar

Snyder, M.F., Rideout, V.C. and Hillestad, R.J. (1968), “Computer modeling of the human systemic arterial tree”, Journal of Biomechanics, Vol. 1 No. 4, pp. 341-353.

DOI Google Scholar

Sornette, D., Davis, A.B., Ide, K., Vixie, K.R., Pisarenko, V. and Kamm, J.R. (2007), “Algorithm for model validation: theory and applications”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 104 No. 16, pp. 6562-6567.

DOI Google Scholar

Sun, H. and Zhang, M. (2017), “An HLA based simulation framework for crowd science”, 2017 International Conference on Mathematics, Modelling and Simulation Technologies and Applications (MMSTA 2017), pp. 714-718.

Tabak, V.V., Vries, D.B.B. and Dijkstra, J.J. (2010), “RFID technology applied for validation of an office simulation model”, Pedestrian and Evacuation Dynamics 2008, pp. 269-275.https://doi.org/10.1007/978-3-642-04504-2_23

DOI

Tang, J.B., Zha, Y.B. and Li, G. (2006), “An overview of the research on VV&A in simulation”,Computer Simulation, Vol. 11 No. 4, pp. 82-86.

Google Scholar

Terano, T. (2006), “Exploring the vast parameter space of multi-agent based simulation”,International Conference on Multi-Agent-Based Simulation VII, Springer-Verlag, pp. 1-14.https://doi.org/10.1007/978-3-540-76539-4_1

DOI

Terano, T. (2007), “Exploring the vast parameter space of multi-agent based simulation”, in Antunes, L. and Takadama, K. (Eds), Multiagent-Based Simulation VII. Lecture Notes in Computer Science, Springer, Berlin Heidelberg, Vol. 4442, pp. 1-14.https://doi.org/10.1007/978-3-540-76539-4_1

DOI

Tian, G.W., Yong, W.U., Dong, Z.J., Bao, T.H. and Tao, J.J. (2012), “A grey theory model using in the simulation credibility evaluation of the integrative avionics system”, Fire Control and Command Control.

Wang, Z., Li, Z., Feng, Y. and Rong, G. (2016), “Crude oil operations under uncertainty: a continuous-time rescheduling framework and a simulation environment for validation”, Industrial and Engineering Chemistry Research, available at: acs.iecr.6b01108https://doi.org/10.1021/acs.iecr.6b01108

DOI

Weisel, E.W. (2004), “Models, composability, and validity”, Doctoral dissertation, Old Dominion University, Norfolk, VA.

Weisel, E.W., Petty, M.D. and Mielke, R.R. (2003), “Validity of models and classes of models in semantic composability”, Proceeding Fall Simulation Interoperability Workshop 2003, Vol. 9, p. 68.

Whitner, R.B. and Balci, O. (1989), “Guidelines for selecting and using simulation model verification techniques”, in MacNair, E.A., Musselman, K.J. and Heidelberger, P. (Eds), Proceedings of the 1989 Winter Simulation Conference, IEEE, Piscataway, NJ, pp. 559-568.https://doi.org/10.1145/76738.76811

DOI

Wigan, M.R. (1972), “Fitting, calibration, and validation of simulation models, simulation”, Vol. 18 No. 5, pp. 188-192.https://doi.org/10.1177/003754977201800506

DOI

Yilmaz, L. and Balci, O. (1997), “Object-oriented simulation model verification and validation”, Proceedings of the 1997 Summer Computer Simulation Conference, SCS, San Diego, CA.

Yu, X.J. and Xiao, R. (2018), “Credibility verification method and calculation based on application behavior declaration”, Computer Systems and Applications, Vol. 27 No. 11, pp. 17-26.

Google Scholar

Zeigler, B.P. and Sarjoughian, H.S. (2002), “Implications of M&S foundations for the V&V of large scale complex simulation models”,Proceedings of the Foundations for V&V in the 21st Century Workshop, Laurel, MD.

Zha, Y. and Kedi, H. (1997), “A survey on the credibility of system simulation”, Journal of System Simulation, Vol. 9 No. 1, pp. 4-9.

Google Scholar

Zhang, S., Geng, H., Tong, J. and Du, M. (2012), “The research review on VV&A working system of complex simulation system”, AsiaSim 2012, pp. 534-539.https://doi.org/10.1007/978-3-642-34384-1_63

DOI

Zhang, W. and Wang, X.R. (2001), “Simulation credibility”, Xitong Fangzhen Xuebao/Acta Simulata Systematica Sinica, Vol. 13 No. 3, pp. 312-314.

Google Scholar

Zoumpoulaki, A., Avradinis, N. and Vosinakis, S. (2010), “A multi-agent simulation framework for emergency evacuations incorporating personality and emotions”, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 6040 LNAI, pp. 423-428.https://doi.org/10.1007/978-3-642-12842-4_54

DOI

Zupan, B., Holmes, J.H. and Bellazzi, R. (2006), “Knowledge-based data analysis and interpretation”, Artificial Intelligence in Medicine, Vol. 37 No. 3, pp. 163-165.

DOI Google Scholar

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Received: 25 January 2019

Accepted: 04 March 2019

Published: 07 May 2019

Issue date: June 2019

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Acknowledgements

This work is supported by the National Key R&D Program of China (Grant No. 2017YFB1400105).

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Yanan Wang, Jianqiang Li, Sun Hongbo, Yuan Li, Faheem Akhtar and Azhar Imran. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode